Jan vs. Ollama: Which Offline AI Interface is Best for You?
Z
Zack Saadioui
8/11/2025
Jan vs. Ollama's New GUI: Which Offline AI Interface is Best for You?
So, you're looking to dive into the world of local, offline AI. Smart move. Keeping your data private & having total control over your models is a game-changer. But as you've probably figured out, the landscape can be a bit… confusing. Two names that keep popping up are Jan & Ollama, especially with Ollama's recent release of an official GUI.
Honestly, it's a hot topic, & for good reason. Both offer a way to run powerful large language models (LLMs) on your own machine, but they go about it in VERY different ways. I’ve spent a good amount of time tinkering with both, so I wanted to break down the real differences, the pros & cons, & hopefully help you figure out which one is the right fit for you.
The Big Picture: Two Philosophies for Local AI
Before we get into the nitty-gritty, it's important to understand the fundamental difference in approach between Jan & Ollama.
Jan is the "all-in-one" solution. Think of it like a ready-to-go appliance. You download one application, & it includes everything you need: the user interface (the part you actually interact with), the backend that runs the models, & a hub for downloading new models. It’s designed to be as user-friendly as possible, especially for those who aren't super technical.
Ollama is the "engine." It's a powerful, lightweight tool that runs in the background, managing & serving the LLMs. By itself, it's a command-line tool, which means you interact with it through text commands. To get a familiar, ChatGPT-like interface, you need to pair it with a separate frontend, the most popular being OpenWebUI. Recently, Ollama also launched its own official, though still basic, GUI. This modular approach is a bit more complex to set up but offers a TON of flexibility.
So, the real comparison isn't just Jan vs. Ollama, but more accurately, Jan vs. the Ollama + GUI experience.
Ease of Use & Setup: Getting Up & Running
This is probably the most significant deciding factor for many people.
Jan:
Getting started with Jan is about as straightforward as it gets. You go to their website, download the installer for your operating system (Windows, Mac, or Linux), & run it. That's pretty much it. Once installed, you have an interface that's clean & polished. You can browse a "hub" of popular models like Llama 3, Mistral, & Gemma, & download them with a single click. It’s designed to feel a lot like using a commercial tool, which is a big plus for beginners.
However, some users have reported that Jan can be a bit clunky, especially on Linux. It's a Tauri app, which is a framework for building desktop applications, & some people find these apps don't feel as "native" as other software. Also, the application itself can be quite large, with one user noting a 1.8GB repository swelling to 4.8GB after building.
Ollama & OpenWebUI:
Here's where the extra flexibility comes with a bit of a learning curve. First, you install Ollama, which is also a simple download from their website. Then, to get the graphical interface, you'll need to install OpenWebUI. The most common way to do this is with Docker, a containerization platform. If you're not familiar with Docker, this can seem intimidating. It involves running a command in your terminal to download & run the OpenWebUI container.
While it's a few more steps, there are tons of great tutorials out there to walk you through it. The benefit of this approach is that Ollama runs as a separate, lightweight service. You can have multiple different frontends connect to it, or even use it directly in your own code.
Recently, Ollama released its own official GUI, which is still in its early stages but offers a much simpler entry point. It’s a very basic interface, but it lets you chat with your models without messing with the command line or Docker. For new users who just want to try out Ollama, this is a fantastic development.
The Verdict on Setup: If you want the absolute easiest, no-fuss setup, Jan is the clear winner. If you're comfortable with a bit more of a technical setup process in exchange for more flexibility, the Ollama + OpenWebUI stack is a powerful combination.
Feature Face-Off: What Can They Actually Do?
Okay, so you've got them installed. What's it actually like to use them?
Jan's GUI:
Jan’s interface is designed to be an all-in-one workspace. Here are some of the key features:
Model Hub: Easily browse & download popular open-source models.
Cloud Model Integration: You can also connect to cloud-based models from OpenAI, Groq, Cohere, etc., by adding your API key. This is great for when you need the power of a model like GPT-4 but want to keep all your interactions in one place.
Local API Server: With one click, you can start a local server that's compatible with OpenAI's API. This is HUGE for developers who want to build applications that use local models.
Chat with Files (Experimental): Jan has an experimental feature for Retrieval-Augmented Generation (RAG), which lets you chat with your own documents. This is super useful for summarizing PDFs or asking questions about your notes.
Custom Assistants: You can create personalized AI assistants that remember your conversations & are tailored for specific tasks.
One of the main complaints about Jan is that it can feel a bit slow & some users have reported that it can't handle multiple conversations at once; if you start a long generation in one chat, you have to wait for it to finish before you can start another.
Ollama with OpenWebUI:
OpenWebUI is an incredibly feature-rich interface that's constantly being updated. It feels very much like a supercharged, self-hosted version of ChatGPT. Here are some of its standout features:
Advanced RAG: OpenWebUI has a very powerful & mature RAG implementation. You can easily upload documents & have the AI use them as a knowledge base for its answers.
Model Builder: You can create custom models directly within the interface, modifying existing models with your own instructions or system prompts.
Extensive Customization: You can fine-tune almost every aspect of your chat experience, from the model parameters to the look & feel of the interface.
Multi-Modal Support: OpenWebUI can handle models that understand images, like LLaVA.
Pipelines & Integrations: OpenWebUI has a modular "pipelines" framework that allows for all sorts of cool integrations, like AI agents or home automation.
Multi-User Support: If you're running this on a server for a team, OpenWebUI has robust user management features.
For businesses looking to integrate AI into their customer service, the combination of Ollama's power & OpenWebUI's feature set is pretty compelling. You could, for instance, create a specialized model trained on your company's documentation. Then, you can build a customer-facing chatbot using a platform like Arsturn. Arsturn helps businesses create custom AI chatbots trained on their own data, providing instant customer support & answering questions 24/7. By connecting an Arsturn chatbot to a locally-hosted model via Ollama, you could have a completely private & highly customized customer service solution.
The Verdict on Features: For a simple, all-in-one experience with good core features, Jan is solid. For power users who want the most advanced features, deep customization, & expandability, Ollama with OpenWebUI is in a league of its own.
Hardware Requirements & Performance
Running LLMs locally is demanding, so your hardware will play a big role in your experience.
Jan:
Jan's website provides some general guidelines:
For smaller models (up to 3B parameters), you'll want at least 8GB of RAM.
For 7B models, 16GB of RAM is recommended.
For 13B models, you'll need 32GB of RAM.
A GPU with at least 6GB of VRAM is recommended for a good experience.
Users have reported that without a GPU, Jan can be quite slow. With GPU acceleration, however, the performance is significantly better. Jan supports NVIDIA GPUs (with CUDA), AMD GPUs, & Intel Arc GPUs.
Ollama & OpenWebUI:
The hardware requirements for Ollama are pretty similar. A decent CPU & at least 16GB of RAM are a good starting point. Where things get interesting is with GPU support. Ollama is very efficient at utilizing GPU VRAM. It can even split models between your GPU's VRAM & your system's RAM, which allows you to run larger models than you might think.
Performance benchmarks have shown that Ollama on an NVIDIA GPU is very fast. It also has good support for AMD GPUs on Linux via ROCm.
The Verdict on Hardware & Performance: Both tools have similar hardware requirements, but Ollama seems to have a slight edge in terms of performance & efficient use of hardware, especially its ability to split models across VRAM & RAM.
Customization & Community
Jan:
Jan is open-source & has a growing community on Discord. They have documentation to help developers integrate LLMs into their systems. Jan is also customizable through an extension framework, which allows you to adjust things like censorship & moderation levels.
Ollama & OpenWebUI:
Being a more modular system, the Ollama ecosystem is incredibly vibrant. Both Ollama & OpenWebUI are open-source projects with massive communities on GitHub & Discord. This means there's a ton of support available, & new features & integrations are being developed all the time. The ability to mix & match different components gives you ultimate control over your setup.
For businesses looking to automate processes or improve their website engagement, this level of customization is a huge advantage. You can build a highly specific AI tool that perfectly fits your needs. For instance, a business could use a fine-tuned model running on Ollama to power a lead generation chatbot on their website. A platform like Arsturn could be used to build this no-code AI chatbot. Arsturn helps businesses build chatbots trained on their own data to boost conversions & provide personalized customer experiences, making it a perfect match for a custom backend like Ollama.
The Verdict on Customization & Community: While Jan offers some good customization options, the modular nature & massive community behind Ollama & OpenWebUI make it the winner for those who want to tinker, customize, & have access to a wealth of community support.
The New Ollama GUI: A Wildcard
It's worth mentioning Ollama's new official GUI again. As of late 2025, it's still pretty basic. It allows you to chat with your models & upload files & images, but it lacks the advanced features of Jan or OpenWebUI. However, it's a clear sign that the Ollama team is focused on making their tool more accessible. For new users, it might be the perfect, simple way to get started with local AI without the overhead of setting up Docker & OpenWebUI. It will be interesting to see how it evolves over time.
So, Which One is for You?
Honestly, there's no single "best" choice. It really comes down to who you are & what you want to do.
Choose Jan if:
You're new to local AI & want the easiest possible setup.
You prefer an all-in-one application that "just works" out of the box.
You want a polished, user-friendly interface & don't mind sacrificing some advanced features for simplicity.
You want to easily switch between local & cloud-based models in one app.
Choose Ollama with OpenWebUI (or another GUI) if:
You're a developer, power user, or tinkerer who wants maximum control & flexibility.
You're comfortable with a more technical setup process involving the command line & Docker.
You want the most feature-rich & customizable experience possible.
You're interested in multi-user support or advanced integrations.
You prioritize performance & want to squeeze every last drop of power out of your hardware.
My Personal Take:
I started with Jan because it was so easy to get going. It was a fantastic introduction to the world of local LLMs. But as I got more curious & wanted to do more, I found myself drawn to the power & flexibility of the Ollama & OpenWebUI stack. The ability to fine-tune everything & the amazing community support have made it my go-to for most projects.
That said, I'm REALLY excited about the new official Ollama GUI. I think it will be a game-changer for a lot of people who were intimidated by the command line.
The best part is, you don't have to choose just one! They're both free to try, so I'd recommend downloading Jan & giving it a spin. Then, if you feel like you're hitting its limits, you can try setting up Ollama.
Hope this was helpful! The world of local AI is moving at an incredible pace, & it's a super exciting time to jump in. Let me know what you think & what your experiences have been.